Learn Machine Learning Classification Algorithms using MATLAB and learn how to implement to use different machine learning algorithms using MATLAB.
Machine learning classification algorithms is one of the most complicated topics to understand but this course is especially designed in a stepwise manner which will cover the basics of MATLAB and will also educate learners on how to use different machine learning algorithms using MATLAB.
This course will be covering classification algorithms such as K-Nearest Neighbor, Naive Bayes, Discriminant Analysis, Decision Tress, Support Vector Machines, Error-Correcting Output Codes and Ensembles. Also, you’ll get to learn how to cross validate these models & evaluate their performances.
Layout of the complete course will be:
Segment 1: Instructor and Course Introduction
Segment 2: MATLAB Crash Course
Segment 3: Grabbing and Importing Dataset
Segment 4: K-Nearest Neighbor
Segment 5: Naive Bayes
Segment 6: Decision Trees
Segment 7: Discriminant Analysis
Segment 8: Support Vector Machines
Segment 9: Error Correcting Output Codes
Segment 10: Classification with Ensembles
Segment 11: Validation Methods
Segment 12: Evaluating Performance
Outcomes on completion of this course:
- In-depth knowledge on implementation of machine learning algorithms using MATLAB
- Effective performing of analysis on the data
Some exceptional benefits associated with this course enrollment are:
- Quality course material
- Lifetime access to the course
- Instant & free course updates
- Access to all Questions & Answers initiated by other students as well
- Personalized support from the instructor’s end on any issue related to the course
- Few free lectures for a quick overview
- Be loud and clear amongst the crowd
- Adapt personality that creates a connection
- Make self-image of audiences at a personal level
It’s time for you to grab the opportunity and make the most out of your life.
This course will be providing various practice options in between the lessons, which you’ll find highly useful for better learning. Just a few minutes a day can transform your career growth.
Don’t miss this unique opportunity